Added info about using SAM with Desktop GIS (#48)

Author: giswqs

README.md

@@ -46,6 +46,11 @@ Video tutorials are available on my [YouTube Channel](https://youtube.com/@giswq
 
 [![Alt text](https://img.youtube.com/vi/YHA_-QMB8_U/0.jpg)](https://www.youtube.com/playlist?list=PLAxJ4-o7ZoPcrg5RnZjkB_KY6tv96WO2h)
 
+## Using SAM with Desktop GIS
+
+-   **QGIS**: Check out the [Geometric Attributes plugin for QGIS](https://github.com/BjornNyberg/Geometric-Attributes-Toolbox/wiki/User-Guide#segment-anything-model). Credit goes to [Bjorn Nyberg](https://github.com/BjornNyberg)
+-   **ArcGIS**: Check out the [Segment Anything Model (SAM) Toolbox for ArcGIS](https://www.arcgis.com/home/item.html?id=9b67b441f29f4ce6810979f5f0667ebe). Credit goes to [Esri](https://www.esri.com).
+
 ## Computing Resources
 
 The Segment Anything Model is computationally intensive, and a powerful GPU is recommended to process large datasets. It is recommended to have a GPU with at least 8 GB of GPU memory. You can utilize the free GPU resources provided by Google Colab. Alternatively, you can apply for [AWS Cloud Credit for Research](https://aws.amazon.com/government-education/research-and-technical-computing/cloud-credit-for-research), which offers cloud credits to support academic research. If you are in the Greater China region, apply for the AWS Cloud Credit [here](https://aws.amazon.com/cn/events/educate_cloud/research-credits).

docs/index.md

@@ -46,6 +46,11 @@ Video tutorials are available on my [YouTube Channel](https://youtube.com/@giswq
 
 [![Alt text](https://img.youtube.com/vi/YHA_-QMB8_U/0.jpg)](https://www.youtube.com/playlist?list=PLAxJ4-o7ZoPcrg5RnZjkB_KY6tv96WO2h)
 
+## Using SAM with Desktop GIS
+
+-   **QGIS**: Check out the [Geometric Attributes plugin for QGIS](https://github.com/BjornNyberg/Geometric-Attributes-Toolbox/wiki/User-Guide#segment-anything-model). Credit goes to [Bjorn Nyberg](https://github.com/BjornNyberg)
+-   **ArcGIS**: Check out the [Segment Anything Model (SAM) Toolbox for ArcGIS](https://www.arcgis.com/home/item.html?id=9b67b441f29f4ce6810979f5f0667ebe). Credit goes to [Esri](https://www.esri.com).
+
 ## Computing Resources
 
 The Segment Anything Model is computationally intensive, and a powerful GPU is recommended to process large datasets. It is recommended to have a GPU with at least 8 GB of GPU memory. You can utilize the free GPU resources provided by Google Colab. Alternatively, you can apply for [AWS Cloud Credit for Research](https://aws.amazon.com/government-education/research-and-technical-computing/cloud-credit-for-research), which offers cloud credits to support academic research. If you are in the Greater China region, apply for the AWS Cloud Credit [here](https://aws.amazon.com/cn/events/educate_cloud/research-credits).